The partial dependence function [1]} of a model \(\hat{f}\)  describes the expected effect of a feature after marginalizing out the effects of all other features.
Partial dependence of a feature set \(X_S\) , \(S\subseteq \lbrace 1,\ldots ,p\rbrace \)  (usually \(|S| = 1\) ) is defined as:
\(PD_S = {E}_{X_{C}}[\hat{f}(x, X_{C})],\) 
